ITK 实例8 孤立连接算法对脑部PNG图像进行二维分割

1 #include "itkIsolatedConnectedImageFilter.h" 2 #include "itkImage.h" 3 #include "itkCastImageFilter.h" 4 #include "itkCurvatureFlowImageFilter.h" 5 #include "itkImageFileReader.h" 6 #include "itkImageFileWriter.h" 7 8 int main( int argc, char *argv[] ) 9 */ 18 //我们使用一个像素类型和一个特殊维来定义图像的类型： 19 typedef float InternalPixelType; 20 const unsigned int Dimension = 2; 21 typedef itk::Image< InternalPixelType, Dimension > InternalImageType; 22 23 //下面几行是对 IsolatedConnectedImageFilter 进行实例化的代码 24 typedef unsigned char OutputPixelType; 25 typedef itk::Image< OutputPixelType, Dimension > OutputImageType; 26 typedef itk::CastImageFilter< InternalImageType, OutputImageType > 27 CastingFilterType; 28 CastingFilterType::Pointer caster = CastingFilterType::New(); 29 30 typedef itk::ImageFileReader< InternalImageType > ReaderType; 31 typedef itk::ImageFileWriter< OutputImageType > WriterType; 32 33 ReaderType::Pointer reader = ReaderType::New(); 34 WriterType::Pointer writer = WriterType::New(); 35 36 reader>SetFileName( "BrainProtonDensitySlice.png" ); 37 writer>SetFileName( " Isolated_baizhi.png" ); 38 39 40 typedef itk::CurvatureFlowImageFilter< InternalImageType, InternalImageType > 41 CurvatureFlowImageFilterType; 42 CurvatureFlowImageFilterType::Pointer smoothing = 43 CurvatureFlowImageFilterType::New(); 44 45 typedef itk::IsolatedConnectedImageFilter<InternalImageType, 46 InternalImageType> ConnectedFilterType; 47 //使用 New( ) 方式对这个类的一个文件进行结构化 48 ConnectedFilterType::Pointer isolatedConnected = ConnectedFilterType::New(); 49 //现在连接管道 50 smoothing>SetInput( reader>GetOutput() ); 51 isolatedConnected>SetInput( smoothing>GetOutput() ); 52 caster>SetInput( isolatedConnected>GetOutput() ); 53 writer>SetInput( caster>GetOutput() ); 54 /*IsolatedConnectedImageFilter 期望用户指定一个门限和两个种子。在这个例子中，我们 55 从命令行得到它们*/ 56 smoothing>SetNumberOfIterations( 5 ); 57 smoothing>SetTimeStep( 0.125 ); 58 59 InternalImageType::IndexType indexSeed1; 60 //白质种子点 61 indexSeed1[0] = atoi( "61" ); 62 indexSeed1[1] = atoi( "140" ); //下门限值（要分割的白质的下门限值） 64 const InternalPixelType lowerThreshold = atof( "150" ); 65 66 InternalImageType::IndexType indexSeed2; 67 //灰质种子点 68 indexSeed2[0] = atoi( "" ); 69 indexSeed2[1] = atoi( "43" ); 70 /*由于在 ConnectedThresholdImageFilter 中，现在我们就必须指定在区域中能被输出像素所 71 接受的亮度值以及至少一个种子点来定义最初的区域*/ 72 isolatedConnected>SetLower( lowerThreshold ); 73 isolatedConnected>AddSeed1( indexSeed1 ); 74 isolatedConnected>AddSeed2( indexSeed2 ); 75 76 isolatedConnected>SetReplaceValue( 255 ); 77 /*writer 上的 Updata() 方法触发管道的运行。通常在出现错误和抛出异议时, 从一个 try / catch 78 模块调用 updata*/ 79 try 80 83 catch( itk::ExceptionObject & excep ) 84 88 /*这个亮度值允许我们对两个区域进行分割，使用 GetIsolatedValue() 方式可以对区域进行恢复*/ 89 std::cout << "Isolated Value Found = "; 90 std::cout << isolatedConnected>GetIsolatedValue() << std::endl; 91 return EXIT_SUCCESS; 92 }

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